Topic Modeling of Candidates

In addition to understanding sentiment surrounding a word, we can also examine the different topics and issues candidates tend to focus on within their campaign speeches. There are different ways in which we can analyze topics. We could simply look at frequency of words and derive a general idea of what candidate may be talking about. We can also examine the frequency with which particular words tend to be associated with one another. From these clusters, we can examine which words are highly correlated with one another and derive topics from these highly clustered words.

General Topics from the 2016 Election

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Here we have our first word cloud. This examines the frequency of words and the more frequently a word occurs, the larger it is in the cloud. We see words related to the American ideal with family, future, jobs, nation, and we see words related to the election with president, world, government, and vote.

## # A tibble: 32 Ă— 3
##    topic      term        beta
##    <int>     <chr>       <dbl>
## 1      1   country 0.008746076
## 2      1   america 0.008611358
## 3      1 president 0.008244758
## 4      1      time 0.006992348
## 5      1       lot 0.006843971
## 6      1      hard 0.005703205
## 7      1  families 0.005641641
## 8      1 americans 0.005227166
## 9      2   country 0.016535323
## 10     2   america 0.006958057
## # ... with 22 more rows
topic term beta
1 1 0.0001667
2 1 0.0017508
3 1 0.0008785
4 1 0.0000352
1 10 0.0008696
2 10 0.0009894
3 10 0.0009346
4 10 0.0005063
1 100,000 0.0000015
2 100,000 0.0000395
3 100,000 0.0001824
4 100,000 0.0001051
1 112 0.0001411
2 112 0.0000489
3 112 0.0000000
4 112 0.0000481
1 125,000 0.0001963
2 125,000 0.0000447
3 125,000 0.0000000
4 125,000 0.0000000
1 15 0.0000825
2 15 0.0010476
3 15 0.0007677
4 15 0.0001041
1 1987 0.0000000
2 1987 0.0000416
3 1987 0.0000000
4 1987 0.0000567
1 250,000 0.0000494
2 250,000 0.0000523
3 250,000 0.0000000
4 250,000 0.0000000
1 26 0.0000817
2 26 0.0000674
3 26 0.0000893
4 26 0.0000000
1 30 0.0005138
2 30 0.0009811
3 30 0.0005978
4 30 0.0002765
1 5th 0.0000343
2 5th 0.0000001
3 5th 0.0000456
4 5th 0.0000000
1 7am 0.0000023
2 7am 0.0000382
3 7am 0.0000000
4 7am 0.0000000
1 7pm 0.0000000
2 7pm 0.0000415
3 7pm 0.0000000
4 7pm 0.0000000
1 9th 0.0000804
2 9th 0.0000485
3 9th 0.0000000
4 9th 0.0000000
1 absurdity 0.0000000
2 absurdity 0.0001248
3 absurdity 0.0000000
4 absurdity 0.0000000
1 accused 0.0000567
2 accused 0.0000000
3 accused 0.0000000
4 accused 0.0000567
1 act 0.0006848
2 act 0.0015297
3 act 0.0000778
4 act 0.0006825
1 acts 0.0000529
2 acts 0.0000293
3 acts 0.0000000
4 acts 0.0003078
1 ad 0.0000000
2 ad 0.0002497
3 ad 0.0000000
4 ad 0.0000000
1 affect 0.0000894
2 affect 0.0000352
3 affect 0.0000000
4 affect 0.0000567
1 affordable 0.0013082
2 affordable 0.0006762
3 affordable 0.0004492
4 affordable 0.0000000
1 afraid 0.0002878
2 afraid 0.0002290
3 afraid 0.0000000
4 afraid 0.0004733
1 ago 0.0013132
2 ago 0.0022719
3 ago 0.0007355
4 ago 0.0009790
1 ahead 0.0017839
2 ahead 0.0004074
3 ahead 0.0000906
4 ahead 0.0002682
1 air 0.0001470
2 air 0.0001368
3 air 0.0003449
4 air 0.0010217
1 alicia 0.0001700
2 alicia 0.0000001
3 alicia 0.0000000
4 alicia 0.0000000
1 alike 0.0001762
2 alike 0.0000000
3 alike 0.0000000
4 alike 0.0000445
1 allegiance 0.0000311
2 allegiance 0.0000000
3 allegiance 0.0000485
4 allegiance 0.0000000
1 amanda 0.0000000
2 amanda 0.0000415
3 amanda 0.0000000
4 amanda 0.0000000
1 america 0.0086114
2 america 0.0069581
3 america 0.0100329
4 america 0.0089567
1 americans 0.0052272
2 americans 0.0033377
3 americans 0.0057287
4 americans 0.0033431
1 angry 0.0001275
2 angry 0.0001908
3 angry 0.0000255
4 angry 0.0001087
1 appeal 0.0000555
2 appeal 0.0000849
3 appeal 0.0000000
4 appeal 0.0000000
1 armed 0.0002817
2 armed 0.0000000
3 armed 0.0001419
4 armed 0.0003122
1 assault 0.0001853
2 assault 0.0000000
3 assault 0.0001345
4 assault 0.0003513
1 assaulting 0.0000008
2 assaulting 0.0000404
3 assaulting 0.0000000
4 assaulting 0.0000000
1 assigned 0.0000000
2 assigned 0.0000416
3 assigned 0.0000000
4 assigned 0.0000000
1 athletes 0.0001417
2 athletes 0.0000000
3 athletes 0.0000000
4 athletes 0.0001134
1 attack 0.0001275
2 attack 0.0002919
3 attack 0.0003937
4 attack 0.0021021
1 attractive 0.0000000
2 attractive 0.0000415
3 attractive 0.0000000
4 attractive 0.0000000
1 backstage 0.0000001
2 backstage 0.0000415
3 backstage 0.0000000
4 backstage 0.0000000
1 backwards 0.0001219
2 backwards 0.0000291
3 backwards 0.0000000
4 backwards 0.0000000
1 bad 0.0006440
2 bad 0.0008788
3 bad 0.0008465
4 bad 0.0006804
1 balance 0.0005138
2 balance 0.0000000
3 balance 0.0000000
4 balance 0.0001630
1 ballot 0.0007857
2 ballot 0.0000149
3 ballot 0.0001508
4 ballot 0.0000577
1 barge 0.0000001
2 barge 0.0000415
3 barge 0.0000000
4 barge 0.0000000
1 barriers 0.0003317
2 barriers 0.0000696
3 barriers 0.0000000
4 barriers 0.0000922
1 basically 0.0005809
2 basically 0.0000437
3 basically 0.0000628
4 basically 0.0000000
1 beautiful 0.0004291
2 beautiful 0.0002231
3 beautiful 0.0003999
4 beautiful 0.0001609
1 beauty 0.0000567
2 beauty 0.0000000
3 beauty 0.0000000
4 beauty 0.0000000
1 begun 0.0000793
2 begun 0.0001532
3 begun 0.0000643
4 begun 0.0000000
1 behalf 0.0006177
2 behalf 0.0000000
3 behalf 0.0003553
4 behalf 0.0002431
1 believing 0.0000494
2 believing 0.0000523
3 believing 0.0001010
4 believing 0.0000024
1 belittling 0.0000567
2 belittling 0.0000000
3 belittling 0.0000000
4 belittling 0.0000000
1 beverly 0.0000001
2 beverly 0.0000415
3 beverly 0.0000000
4 beverly 0.0000000
1 bigger 0.0003878
2 bigger 0.0002110
3 bigger 0.0004915
4 bigger 0.0004532
1 biggest 0.0010177
2 biggest 0.0001199
3 biggest 0.0009697
4 biggest 0.0002397
1 bill 0.0008592
2 bill 0.0011356
3 bill 0.0026135
4 bill 0.0000000
1 bills 0.0001692
2 bills 0.0000000
3 bills 0.0001836
4 bills 0.0000475
1 bin 0.0001513
2 bin 0.0000310
3 bin 0.0000137
4 bin 0.0002484
1 birth 0.0001323
2 birth 0.0001387
3 birth 0.0000000
4 birth 0.0000000
1 blair 0.0000567
2 blair 0.0000000
3 blair 0.0000000
4 blair 0.0000000
1 blame 0.0001755
2 blame 0.0000000
3 blame 0.0000766
4 blame 0.0000458
1 bodies 0.0000000
2 bodies 0.0000416
3 bodies 0.0000000
4 bodies 0.0001702
1 born 0.0005047
2 born 0.0003786
3 born 0.0000000
4 born 0.0003458
1 bossy 0.0000002
2 bossy 0.0000413
3 bossy 0.0000000
4 bossy 0.0000000
1 bottom 0.0001050
2 bottom 0.0013835
3 bottom 0.0001511
4 bottom 0.0004041
1 boys 0.0001701
2 boys 0.0000000
3 boys 0.0000000
4 boys 0.0000000
1 bragging 0.0001178
2 bragging 0.0000001
3 bragging 0.0000000
4 bragging 0.0000477
1 break 0.0004541
2 break 0.0003243
3 break 0.0008620
4 break 0.0001938
1 bring 0.0012546
2 bring 0.0016883
3 bring 0.0027787
4 bring 0.0014917
1 bringing 0.0002279
2 bringing 0.0006513
3 bringing 0.0001935
4 bringing 0.0002683
1 brought 0.0007046
2 brought 0.0001943
3 brought 0.0004124
4 brought 0.0004149
1 bruce 0.0000850
2 bruce 0.0000000
3 bruce 0.0000000
4 bruce 0.0000000
1 bully 0.0001106
2 bully 0.0000000
3 bully 0.0000433
4 bully 0.0001929
1 bunch 0.0001701
2 bunch 0.0000000
3 bunch 0.0000000
4 bunch 0.0000000
1 bunker 0.0000001
2 bunker 0.0000415
3 bunker 0.0000000
4 bunker 0.0000000
1 called 0.0018842
2 called 0.0013841
3 called 0.0010879
4 called 0.0008872
1 calls 0.0003140
2 calls 0.0003998
3 calls 0.0003526
4 calls 0.0003688
1 calmness 0.0000000
2 calmness 0.0000416
3 calmness 0.0000000
4 calmness 0.0000000
1 campaign 0.0040001
2 campaign 0.0066719
3 campaign 0.0033151
4 campaign 0.0006614
1 capabilities 0.0000000
2 capabilities 0.0001248
3 capabilities 0.0000000
4 capabilities 0.0005672
1 capable 0.0001137
2 capable 0.0000000
3 capable 0.0000766
4 capable 0.0001127
1 captain 0.0000863
2 captain 0.0000000
3 captain 0.0000232
4 captain 0.0002296
1 care 0.0049597
2 care 0.0037548
3 care 0.0015928
4 care 0.0002493
1 cared 0.0001099
2 cared 0.0000468
3 cared 0.0000000
4 cared 0.0000567
1 career 0.0004206
2 career 0.0001851
3 career 0.0003909
4 career 0.0000794
1 casually 0.0000002
2 casually 0.0000414
3 casually 0.0000000
4 casually 0.0000000
1 center 0.0002791
2 center 0.0000001
3 center 0.0005814
4 center 0.0003046
1 certificate 0.0000567
2 certificate 0.0000000
3 certificate 0.0000000
4 certificate 0.0000000
1 chair 0.0000567
2 chair 0.0000000
3 chair 0.0000000
4 chair 0.0000000
1 chairman 0.0000003
2 chairman 0.0002455
3 chairman 0.0000788
4 chairman 0.0000000
1 challenges 0.0011094
2 challenges 0.0002252
3 challenges 0.0000954
4 challenges 0.0007210
1 chamber 0.0000000
2 chamber 0.0000416
3 chamber 0.0000000
4 chamber 0.0000000
1 change 0.0020927
2 change 0.0037727
3 change 0.0029271
4 change 0.0013511
1 changing 0.0001917
2 changing 0.0000000
3 changing 0.0000826
4 changing 0.0000000
1 charge 0.0001836
2 charge 0.0004703
3 charge 0.0001137
4 charge 0.0003837
1 chelsea 0.0001701
2 chelsea 0.0000000
3 chelsea 0.0000000
4 chelsea 0.0000000
1 chief 0.0005725
2 chief 0.0000039
3 chief 0.0002522
4 chief 0.0005574
1 child 0.0024374
2 child 0.0005028
3 child 0.0021167
4 child 0.0000001
1 childcare 0.0010255
2 childcare 0.0000000
3 childcare 0.0008123
4 childcare 0.0000000
1 children 0.0039262
2 children 0.0012776
3 children 0.0026147
4 children 0.0013811
1 choice 0.0008717
2 choice 0.0000018
3 choice 0.0026073
4 choice 0.0006836
1 choosing 0.0000000
2 choosing 0.0000688
3 choosing 0.0000000
4 choosing 0.0001897
1 churchgoer 0.0000000
2 churchgoer 0.0000416
3 churchgoer 0.0000000
4 churchgoer 0.0000000
1 city 0.0006734
2 city 0.0004300
3 city 0.0012026
4 city 0.0003286
1 clean 0.0011596
2 clean 0.0004469
3 clean 0.0002642
4 clean 0.0000000
1 clearer 0.0000850
2 clearer 0.0000000
3 clearer 0.0000000
4 clearer 0.0000000
1 clothes 0.0000850
2 clothes 0.0000000
3 clothes 0.0000000
4 clothes 0.0000000
1 codes 0.0001405
2 codes 0.0000319
3 codes 0.0000000
4 codes 0.0000724
1 college 0.0029144
2 college 0.0012823
3 college 0.0003354
4 college 0.0001833
1 colonel 0.0000000
2 colonel 0.0000416
3 colonel 0.0000000
4 colonel 0.0000567
1 color 0.0004628
2 color 0.0003193
3 color 0.0001276
4 color 0.0000000
1 coming 0.0011327
2 coming 0.0009277
3 coming 0.0004769
4 coming 0.0006841
1 commander 0.0004972
2 commander 0.0000000
3 commander 0.0000992
4 commander 0.0005997
1 comment 0.0001099
2 comment 0.0000467
3 comment 0.0000255
4 comment 0.0000000
1 commerce 0.0000268
2 commerce 0.0000028
3 commerce 0.0001528
4 commerce 0.0000000
1 committee 0.0001041
2 committee 0.0008440
3 committee 0.0000000
4 committee 0.0000593
1 conclude 0.0000000
2 conclude 0.0004107
3 conclude 0.0000782
4 conclude 0.0003440
1 conclusively 0.0000828
2 conclusively 0.0000033
3 conclusively 0.0000000
4 conclusively 0.0000000
1 confidence 0.0004113
2 confidence 0.0000000
3 confidence 0.0000312
4 confidence 0.0001855
1 congress 0.0009237
2 congress 0.0018233
3 congress 0.0017234
4 congress 0.0010819
1 consequential 0.0001701
2 consequential 0.0000000
3 consequential 0.0000000
4 consequential 0.0000000
1 contestants 0.0000000
2 contestants 0.0000832
3 contestants 0.0000000
4 contestants 0.0000000
1 contrast 0.0001712
2 contrast 0.0000000
3 contrast 0.0001516
4 contrast 0.0000579
1 convention 0.0005206
2 convention 0.0001399
3 convention 0.0000835
4 convention 0.0000000
1 core 0.0003158
2 core 0.0002169
3 core 0.0006914
4 core 0.0004854
1 corporations 0.0007732
2 corporations 0.0010496
3 corporations 0.0005232
4 corporations 0.0000000
1 counter 0.0000626
2 counter 0.0000610
3 counter 0.0000000
4 counter 0.0004721
1 countries 0.0009909
2 countries 0.0012862
3 countries 0.0022942
4 countries 0.0033035
1 country 0.0087461
2 country 0.0165353
3 country 0.0154376
4 country 0.0054581
1 county 0.0004660
2 county 0.0005624
3 county 0.0001033
4 county 0.0000000
1 cox 0.0000005
2 cox 0.0000408
3 cox 0.0000000
4 cox 0.0000000
1 create 0.0012789
2 create 0.0028045
3 create 0.0015442
4 create 0.0004528
1 criticism 0.0000867
2 criticism 0.0000000
3 criticism 0.0000000
4 criticism 0.0001102
1 criticize 0.0000925
2 criticize 0.0000723
3 criticize 0.0000000
4 criticize 0.0000567
1 crowd 0.0002371
2 crowd 0.0001513
3 crowd 0.0000000
4 crowd 0.0000000
1 dade 0.0000000
2 dade 0.0000416
3 dade 0.0000000
4 dade 0.0000000
1 dangerous 0.0003835
2 dangerous 0.0001016
3 dangerous 0.0004783
4 dangerous 0.0006970
1 daughter 0.0007153
2 daughter 0.0000835
3 daughter 0.0001128
4 daughter 0.0001328
1 day 0.0035369
2 day 0.0022636
3 day 0.0023215
4 day 0.0014676
1 days 0.0028114
2 days 0.0003385
3 days 0.0015353
4 days 0.0006543
1 debates 0.0003240
2 debates 0.0001070
3 debates 0.0000510
4 debates 0.0000000
1 debt 0.0019690
2 debt 0.0008422
3 debt 0.0006688
4 debt 0.0003456
1 decide 0.0003690
2 decide 0.0001056
3 decide 0.0001674
4 decide 0.0000504
1 defending 0.0001820
2 defending 0.0000657
3 defending 0.0000000
4 defending 0.0002836
1 definition 0.0001146
2 definition 0.0000465
3 definition 0.0000470
4 definition 0.0000000
1 defrauded 0.0001117
2 defrauded 0.0000025
3 defrauded 0.0000000
4 defrauded 0.0000000
1 degrading 0.0000001
2 degrading 0.0000415
3 degrading 0.0000000
4 degrading 0.0000000
1 delighted 0.0002082
2 delighted 0.0000001
3 delighted 0.0000260
4 delighted 0.0000928
1 demeaning 0.0000000
2 demeaning 0.0000416
3 demeaning 0.0000000
4 demeaning 0.0000000
1 democratic 0.0008923
2 democratic 0.0022180
3 democratic 0.0007092
4 democratic 0.0003081
1 democrats 0.0009985
2 democrats 0.0009319
3 democrats 0.0005897
4 democrats 0.0004695
1 develop 0.0000763
2 develop 0.0002311
3 develop 0.0000867
4 develop 0.0013248
1 died 0.0002115
2 died 0.0001745
3 died 0.0001650
4 died 0.0001633
1 difference 0.0011921
2 difference 0.0002656
3 difference 0.0000504
4 difference 0.0004305
1 dinner 0.0000309
2 dinner 0.0002896
3 dinner 0.0000242
4 dinner 0.0000000
1 disgusting 0.0000001
2 disgusting 0.0000414
3 disgusting 0.0000000
4 disgusting 0.0000000
1 distinguished 0.0001134
2 distinguished 0.0000000
3 distinguished 0.0000000
4 distinguished 0.0000000
1 divisive 0.0004198
2 divisive 0.0000167
3 divisive 0.0000000
4 divisive 0.0001014
1 donald 0.0038302
2 donald 0.0024771
3 donald 0.0005372
4 donald 0.0017188
1 donald’s 0.0000833
2 donald’s 0.0000071
3 donald’s 0.0000000
4 donald’s 0.0000504
1 doors 0.0003212
2 doors 0.0000971
3 doors 0.0001617
4 doors 0.0000000
1 dozens 0.0000014
2 dozens 0.0001241
3 dozens 0.0000530
4 dozens 0.0002206
1 dreams 0.0006497
2 dreams 0.0000000
3 dreams 0.0005584
4 dreams 0.0000684
1 dressed 0.0000000
2 dressed 0.0000415
3 dressed 0.0000000
4 dressed 0.0000000
1 drive 0.0004430
2 drive 0.0000979
3 drive 0.0001801
4 drive 0.0001115
1 east 0.0000000
2 east 0.0003784
3 east 0.0005080
4 east 0.0032331
1 eat 0.0002895
2 eat 0.0000479
3 eat 0.0000000
4 eat 0.0000361
1 economic 0.0009300
2 economic 0.0021131
3 economic 0.0019350
4 economic 0.0009979
1 economy 0.0043596
2 economy 0.0041378
3 economy 0.0010237
4 economy 0.0008313
1 elect 0.0004736
2 elect 0.0003008
3 elect 0.0002723
4 elect 0.0000790
1 elected 0.0007539
2 elected 0.0008509
3 elected 0.0003957
4 elected 0.0007062
1 election 0.0040852
2 election 0.0022806
3 election 0.0016309
4 election 0.0003506
1 elections 0.0003570
2 elections 0.0007468
3 elections 0.0001592
4 elections 0.0001262
1 elementary 0.0000620
2 elementary 0.0000000
3 elementary 0.0000208
4 elementary 0.0000565
1 elton 0.0000000
2 elton 0.0000416
3 elton 0.0000000
4 elton 0.0000000
1 employers 0.0002749
2 employers 0.0002622
3 employers 0.0000000
4 employers 0.0000000
1 energy 0.0012219
2 energy 0.0028918
3 energy 0.0031796
4 energy 0.0001031
1 engage 0.0000697
2 engage 0.0003896
3 engage 0.0000000
4 engage 0.0002370
1 entire 0.0007525
2 entire 0.0004605
3 entire 0.0005736
4 entire 0.0005057
1 environment 0.0000743
2 environment 0.0003585
3 environment 0.0000960
4 environment 0.0000000
1 equal 0.0009186
2 equal 0.0001839
3 equal 0.0001552
4 equal 0.0001188
1 ethic 0.0000335
2 ethic 0.0000028
3 ethic 0.0000000
4 ethic 0.0000426
1 excited 0.0009950
2 excited 0.0001623
3 excited 0.0000000
4 excited 0.0000000
1 executive 0.0001750
2 executive 0.0006759
3 executive 0.0004998
4 executive 0.0000000
1 exercise 0.0001236
2 exercise 0.0000680
3 exercise 0.0000000
4 exercise 0.0000571
1 explain 0.0002777
2 explain 0.0000000
3 explain 0.0000047
4 explain 0.0002847
1 exploited 0.0000000
2 exploited 0.0000832
3 exploited 0.0000000
4 exploited 0.0000567
1 eyes 0.0002601
2 eyes 0.0001170
3 eyes 0.0000000
4 eyes 0.0002277
1 fair 0.0016133
2 fair 0.0013290
3 fair 0.0005155
4 fair 0.0003377
1 fairer 0.0003856
2 fairer 0.0001196
3 fairer 0.0000000
4 fairer 0.0000296
1 families 0.0056416
2 families 0.0034469
3 families 0.0013373
4 families 0.0008933
1 family 0.0044254
2 family 0.0036872
3 family 0.0018710
4 family 0.0001683
1 farther 0.0000000
2 farther 0.0000416
3 farther 0.0000000
4 farther 0.0000000
1 fate 0.0000146
2 fate 0.0000207
3 fate 0.0001018
4 fate 0.0000000
1 fault 0.0000000
2 fault 0.0000832
3 fault 0.0000255
4 fault 0.0000000
1 federal 0.0009404
2 federal 0.0010318
3 federal 0.0018057
4 federal 0.0005265
1 feel 0.0015160
2 feel 0.0001496
3 feel 0.0000558
4 feel 0.0004956
1 feels 0.0002208
2 feels 0.0000000
3 feels 0.0000820
4 feels 0.0000000
1 fight 0.0017871
2 fight 0.0023939
3 fight 0.0027692
4 fight 0.0014706
1 fighting 0.0009589
2 fighting 0.0007965
3 fighting 0.0013195
4 fighting 0.0003025
1 figure 0.0009456
2 figure 0.0000476
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4 orbit 0.0000000
1 philippines 0.0000000
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1 policymaking 0.0000000
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3 policymaking 0.0000510
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1 resign 0.0000000
2 resign 0.0000000
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1 2.8 0.0000000
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1 alternate 0.0000000
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1 concede 0.0000000
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1 concession 0.0000000
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1 franchise 0.0000000
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4 franchise 0.0000000
1 hesitation 0.0000000
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4 hesitation 0.0000000
1 inaccurate 0.0000000
2 inaccurate 0.0000000
3 inaccurate 0.0000510
4 inaccurate 0.0000000
1 incite 0.0000000
2 incite 0.0000000
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4 incite 0.0000000
1 invalid 0.0000000
2 invalid 0.0000000
3 invalid 0.0000255
4 invalid 0.0000000
1 licenses 0.0000000
2 licenses 0.0000000
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4 licenses 0.0000000
1 questionable 0.0000000
2 questionable 0.0000000
3 questionable 0.0000255
4 questionable 0.0000000
1 recount 0.0000000
2 recount 0.0000000
3 recount 0.0000510
4 recount 0.0000000
1 registrations 0.0000000
2 registrations 0.0000000
3 registrations 0.0000766
4 registrations 0.0000000
1 rodham 0.0000000
2 rodham 0.0000000
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4 rodham 0.0000000
1 triggered 0.0000000
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4 triggered 0.0000000
1 waive 0.0000000
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1 111th 0.0000000
2 111th 0.0000000
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4 111th 0.0000000
1 14,177 0.0000000
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4 14,177 0.0000000
1 2.75 0.0000000
2 2.75 0.0000000
3 2.75 0.0000255
4 2.75 0.0000000
1 5.1 0.0000000
2 5.1 0.0000000
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4 5.1 0.0000000
1 60th 0.0000000
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4 60th 0.0000000
1 96 0.0000000
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4 96 0.0000000
1 allis 0.0000000
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4 allis 0.0000000
1 altering 0.0000000
2 altering 0.0000000
3 altering 0.0000255
4 altering 0.0000000
1 bleaching 0.0000000
2 bleaching 0.0000000
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4 bleaching 0.0000000
1 briggs 0.0000000
2 briggs 0.0000000
3 briggs 0.0000255
4 briggs 0.0000000
1 carolina’s 0.0000000
2 carolina’s 0.0000000
3 carolina’s 0.0000255
4 carolina’s 0.0000000
1 classify 0.0000000
2 classify 0.0000000
3 classify 0.0000255
4 classify 0.0000000
1 deceased 0.0000000
2 deceased 0.0000000
3 deceased 0.0000255
4 deceased 0.0000000
1 disappearance 0.0000000
2 disappearance 0.0000000
3 disappearance 0.0000255
4 disappearance 0.0000000
1 dwellers 0.0000000
2 dwellers 0.0000000
3 dwellers 0.0000255
4 dwellers 0.0000000
1 exclamation 0.0000000
2 exclamation 0.0000000
3 exclamation 0.0000255
4 exclamation 0.0000000
1 filibusters 0.0000000
2 filibusters 0.0000000
3 filibusters 0.0000255
4 filibusters 0.0000000
1 freeing 0.0000000
2 freeing 0.0000000
3 freeing 0.0000255
4 freeing 0.0000000
1 labeling 0.0000000
2 labeling 0.0000000
3 labeling 0.0000255
4 labeling 0.0000000
1 magnitudes 0.0000000
2 magnitudes 0.0000000
3 magnitudes 0.0000255
4 magnitudes 0.0000000
1 newly 0.0000000
2 newly 0.0000000
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4 newly 0.0000000
1 plausibly 0.0000000
2 plausibly 0.0000000
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1 poison 0.0000000
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4 poison 0.0000000
1 pressured 0.0000000
2 pressured 0.0000000
3 pressured 0.0000255
4 pressured 0.0000000
1 quid 0.0000000
2 quid 0.0000000
3 quid 0.0000255
4 quid 0.0000000
1 sample 0.0000000
2 sample 0.0000000
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4 sample 0.0000000
1 samples 0.0000000
2 samples 0.0000000
3 samples 0.0000255
4 samples 0.0000000
1 scheming 0.0000000
2 scheming 0.0000000
3 scheming 0.0000255
4 scheming 0.0000000
1 sever 0.0000000
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4 sever 0.0000000
1 staffs 0.0000000
2 staffs 0.0000000
3 staffs 0.0000255
4 staffs 0.0000000
1 stratton 0.0000000
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4 stratton 0.0000000
1 tended 0.0000000
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4 tended 0.0000000
1 validity 0.0000000
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3 validity 0.0000255
4 validity 0.0000000
1 87,000 0.0000000
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4 87,000 0.0000000
1 casey 0.0000000
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4 casey 0.0000000
1 chadwick 0.0000000
2 chadwick 0.0000000
3 chadwick 0.0000255
4 chadwick 0.0000000
1 eighties 0.0000000
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4 eighties 0.0000000
1 forestry 0.0000000
2 forestry 0.0000000
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4 forestry 0.0000000
1 newjobs 0.0000000
2 newjobs 0.0000000
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4 newjobs 0.0000000
1 overreach 0.0000000
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4 overreach 0.0000000
1 prosecution 0.0000000
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4 prosecution 0.0000000
1 sixties 0.0000000
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4 sixties 0.0000000
1 stroke 0.0000000
2 stroke 0.0000000
3 stroke 0.0000255
4 stroke 0.0000000
We decid ed to start with assu ming that there were only 4 topics from which campaign revolved around.
Topic 1: Campaign topic with vote, election, and president.
Topic 2: This second topic se ems to be creating a sense of ingroup for Americans
Topic 3: This seems to refer to the American Ideals of family and hard work
Topic 4: America’s economy wi thin an international frameworrk

We can test to see how the accuracy of using four models is compared to using a number of other models. With this tool of perplexity, we can determine what the ideal number of topics it is that we should use. The lower the perplexity score, the more accurate our model will be. From this, we can determine that 15 is much more accurate than 4 while also not being completely overwhelming in trying to determine what the topics actually are.

topic term beta
1 kids 0.0121906
1 lot 0.0098393
1 country 0.0094484
1 care 0.0092986
1 school 0.0084312
2 american 0.0236497
2 hillary 0.0174104
2 clinton 0.0167939
2 country 0.0158416
2 jobs 0.0132548
3 country 0.0095773
3 president 0.0093627
3 americans 0.0084618
3 families 0.0072952
3 time 0.0071952
4 country 0.0087883
4 president 0.0085892
4 lot 0.0063946
4 donald 0.0059654
4 hard 0.0058153
5 america 0.0118192
5 world 0.0109769
5 allies 0.0081825
5 foreign 0.0070836
5 military 0.0067224
6 american 0.0157291
6 country 0.0135331
6 clinton 0.0102721
6 jobs 0.0088575
6 hillary 0.0087541
7 america 0.0134695
7 country 0.0097443
7 world 0.0096908
7 president 0.0090926
7 climate 0.0071157
8 america 0.0112871
8 country 0.0109390
8 trump 0.0090154
8 jobs 0.0084359
8 president 0.0082581
9 country 0.0215462
9 campaign 0.0108946
9 america 0.0081904
9 political 0.0076926
9 percent 0.0072168
10 country 0.0114740
10 trump 0.0087995
10 president 0.0082363
10 clinton 0.0064977
10 hillary 0.0060137
11 america 0.0106432
11 country 0.0098780
11 americans 0.0082578
11 hard 0.0080451
11 economy 0.0078695
12 country 0.0116013
12 time 0.0090041
12 jobs 0.0076882
12 america 0.0073675
12 american 0.0068578
13 clinton 0.0148109
13 president 0.0102852
13 trump 0.0084870
13 donald 0.0072667
13 time 0.0066488
14 clinton 0.0181529
14 hillary 0.0178817
14 country 0.0158886
14 jobs 0.0145241
14 american 0.0131724
15 israel 0.0248724
15 isis 0.0110713
15 united 0.0097722
15 iran 0.0088484
15 president 0.0077045
## [1] 1263.562

Topic 1: Jobs and the Economy Topic 2: Future and the Children Topic 3: Educational Opportunity Topic 4: American Jobs Topic 5: Israel and Foreign Policy Topic 6: Election Topic 7: Economy and Taxes Topic 8: Healthcare Topic 9: Election Topic 10: Wall Street … Topic 15: Terrorism

Now, due to the asymmetry in campaign speeches that we pulled from, Donald Trump’s topics dominate due to the sheer number of speeches compared to the other 3 groups. To counter this, we examine the inverse document frequency which places more value on words used less frequently. The idea is to find an optimal balance between use and weight.

## Warning: Ignoring unknown parameters: scales

This graph shows us the highest weight words based upon use and weight. The large term that seems to emerge is Israel, but you can see how each candidate has certain words seem to be important from their speeches. To better flush out individual candidates inverse term frequency words, we can examine the graph below.

## Selecting by tf_idf

We can now better examine these different ideas that seem to be hidden, yet important in the candidates’ speeches. These are the words with importance, yet they may not be used as frequently as American or President.

With these ideas and tools, we can now model each of the candidates’ topic separately to get a better grasp at the policy and issues that are important to them

Topic Modeling For Donald Trump

## Joining, by = "word"
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## $n, : regulations could not be fit on page. It will not be plotted.
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topic term beta
1 energy 0.0163625
1 jobs 0.0116288
1 american 0.0102629
1 cyber 0.0089480
1 country 0.0088370
1 security 0.0070047
1 government 0.0065641
2 jobs 0.0151849
2 country 0.0140962
2 hillary 0.0137168
2 america 0.0126442
2 american 0.0125379
2 clinton 0.0109355
2 government 0.0096497
3 american 0.0163111
3 country 0.0145832
3 veterans 0.0117136
3 america 0.0106047
3 hillary 0.0103169
3 clinton 0.0081116
3 va 0.0077224
4 american 0.0182538
4 country 0.0156347
4 jobs 0.0113511
4 hillary 0.0109963
4 clinton 0.0106202
4 time 0.0103258
4 african 0.0096802
5 country 0.0122743
5 radical 0.0120748
5 president 0.0112653
5 immigration 0.0110591
5 terrorism 0.0104081
5 isis 0.0104012
5 hillary 0.0097457
6 trump 0.0146970
6 country 0.0095644
6 world 0.0093763
6 military 0.0088997
6 china 0.0077091
6 president 0.0076876
6 foreign 0.0072110
7 hillary 0.0271841
7 clinton 0.0256762
7 country 0.0159460
7 american 0.0129579
7 america 0.0113832
7 jobs 0.0082360
7 americans 0.0078321
8 clinton 0.0181807
8 hillary 0.0132894
8 country 0.0128246
8 government 0.0108185
8 corruption 0.0076648
8 establishment 0.0073392
8 justice 0.0065978
9 american 0.0289240
9 jobs 0.0274972
9 trade 0.0146817
9 country 0.0131056
9 america 0.0109533
9 plan 0.0100144
9 rebuild 0.0077315
10 israel 0.0356855
10 deal 0.0202512
10 iran 0.0186651
10 president 0.0147276
10 united 0.0146601
10 america 0.0109274
10 happen 0.0097583
11 american 0.0141366
11 school 0.0116758
11 country 0.0115510
11 choice 0.0093614
11 plan 0.0080972
11 america 0.0079171
11 education 0.0074444
12 clinton 0.0167767
12 country 0.0128079
12 american 0.0123236
12 hillary 0.0116472
12 percent 0.0100220
12 family 0.0068931
12 america 0.0063064
13 american 0.0335294
13 clinton 0.0311834
13 hillary 0.0272382
13 country 0.0175561
13 jobs 0.0170917
13 america 0.0108699
13 campaign 0.0080141
14 country 0.0179058
14 clinton 0.0152954
14 jobs 0.0149541
14 hillary 0.0140811
14 america 0.0136248
14 american 0.0097327
14 president 0.0079180
15 country 0.0176364
15 america 0.0133015
15 trade 0.0089710
15 american 0.0083732
15 americans 0.0076075
15 world 0.0065973
15 hillary 0.0065060
## [1] 1809.871

Topic Modeling For Hillary Clinton

## Joining, by = "word"
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## plotted.
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## clinton_word_cloud$n, : including could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : challenges could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : heart could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : leaders could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : left could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : schools could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : difference could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : economic could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : stay could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : growth could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : laughter could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : leadership could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : progress could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : story could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : students could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : democratic could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : forward could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : republican could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : student could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : america's could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : democrats could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : history could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : meet could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : past could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : send could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : common could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : deserve could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : fighting could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : grandchildren could not be fit on page. It will not
## be plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : income could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : move could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : potential could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : sanders could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : hands could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : protect could not be fit on page. It will not be
## plotted.
## Warning in wordcloud(words = clinton_word_cloud$word, freq =
## clinton_word_cloud$n, : registered could not be fit on page. It will not be
## plotted.

topic term beta
1 country 0.0104895
1 america 0.0096154
1 families 0.0083042
1 life 0.0078671
1 lot 0.0069930
1 time 0.0069930
1 election 0.0065559
2 american 0.0115703
2 isis 0.0110622
2 country 0.0095135
2 terrorists 0.0079757
2 law 0.0079507
2 community 0.0068906
2 enforcement 0.0068906
3 voting 0.0098488
3 vote 0.0088239
3 country 0.0081938
3 american 0.0073291
3 america 0.0063328
3 rights 0.0061296
3 tax 0.0061294
4 america 0.0111939
4 country 0.0107687
4 lot 0.0085853
4 president 0.0084041
4 jobs 0.0082665
4 pay 0.0081407
4 american 0.0075225
5 growth 0.0148718
5 americans 0.0117949
5 economy 0.0112821
5 president 0.0107692
5 hard 0.0087179
5 term 0.0082051
5 america 0.0076923
5 jobs 0.0076923
6 america 0.0122859
6 president 0.0111690
6 americans 0.0107967
6 country 0.0104244
6 hard 0.0081906
6 families 0.0078183
6 women 0.0067014
7 country 0.0115942
7 america 0.0067633
7 jobs 0.0067633
7 money 0.0067633
7 care 0.0062802
7 families 0.0062802
7 called 0.0057971
7 republicans 0.0057971
8 country 0.0144092
8 america 0.0138329
8 president 0.0115274
8 trump 0.0097983
8 donald 0.0086455
8 americans 0.0063401
8 jobs 0.0063401
9 donald 0.0154582
9 climate 0.0117777
9 america 0.0106735
9 change 0.0080972
9 president 0.0080972
9 trump 0.0077291
9 country 0.0069930
10 clinton 0.0171206
10 president 0.0104017
10 lot 0.0098931
10 question 0.0083565
10 hard 0.0073317
10 time 0.0072592
10 hampshire 0.0062286
11 america 0.0099950
11 families 0.0099950
11 country 0.0094953
11 time 0.0089955
11 election 0.0079960
11 jobs 0.0069965
11 school 0.0069965
12 trump 0.0164943
12 donald 0.0163800
12 president 0.0123437
12 america 0.0114671
12 women 0.0097583
12 country 0.0095697
12 nuclear 0.0085641
13 america 0.0122378
13 israel 0.0104895
13 country 0.0084499
13 president 0.0075758
13 american 0.0075758
13 future 0.0067016
13 jobs 0.0064103
14 service 0.0157201
14 president 0.0126775
14 americans 0.0116633
14 country 0.0116633
14 america 0.0106491
14 time 0.0081136
14 campaign 0.0076065
14 days 0.0076065
14 kids 0.0076065
15 kids 0.0223662
15 school 0.0128675
15 lot 0.0111050
15 education 0.0100241
15 parents 0.0081229
15 care 0.0080108
15 disabilities 0.0078365
## [1] 915.2406

Topic Modeling For Bernie Sanders

## Joining, by = "word"

topic term beta
1 wall 0.0321918
1 street 0.0315068
1 financial 0.0219178
1 banks 0.0136986
1 percent 0.0109589
1 americans 0.0102740
1 country 0.0102740
2 sanders 0.0312815
2 country 0.0252270
2 inskeep 0.0221998
2 democratic 0.0131181
2 clinton 0.0121090
2 donald 0.0121090
2 question 0.0121090
2 county 0.0121090
3 country 0.0206924
3 family 0.0127338
3 america 0.0099483
3 talk 0.0099483
3 campaign 0.0091524
3 percent 0.0091524
3 money 0.0079586
4 country 0.0144371
4 world 0.0074673
4 america 0.0068920
4 millions 0.0066591
4 percent 0.0065741
4 means 0.0063239
4 political 0.0063114
5 isis 0.0257824
5 israel 0.0229008
5 peace 0.0163434
5 region 0.0155046
5 united 0.0132195
5 iran 0.0125942
5 military 0.0103665
6 country 0.0174564
6 campaign 0.0137157
6 vote 0.0137157
6 president 0.0112219
6 road 0.0112219
6 street 0.0099751
6 wall 0.0099751
6 congress 0.0099751
7 country 0.0233677
7 clinton 0.0219167
7 hillary 0.0191747
7 campaign 0.0182885
7 america 0.0163972
7 percent 0.0146013
7 election 0.0117764
8 election 0.0253284
8 americans 0.0253018
8 health 0.0199727
8 leadership 0.0179793
8 future 0.0164074
8 donald 0.0145562
8 wage 0.0144041
9 economy 0.0268362
9 financial 0.0225989
9 pope 0.0169492
9 world 0.0141243
9 common 0.0127119
9 moral 0.0098870
9 political 0.0098870
9 time 0.0098870
9 wealth 0.0098870
10 united 0.0386847
10 palestinian 0.0338873
10 recent 0.0320231
10 world 0.0304256
10 easy 0.0273662
10 sustainable 0.0177359
10 nation 0.0138499
11 country 0.0229265
11 workers 0.0134862
11 america 0.0128119
11 trade 0.0128119
11 millions 0.0121376
11 care 0.0114633
11 health 0.0101146
12 country 0.0260618
12 movement 0.0250965
12 campaign 0.0193050
12 political 0.0115830
12 american 0.0086873
12 class 0.0086873
12 system 0.0086873
13 country 0.0320151
13 justice 0.0169492
13 immigration 0.0150659
13 racism 0.0094162
13 america 0.0084746
13 families 0.0084746
13 united 0.0084746
13 world 0.0084746
13 human 0.0084746
13 talk 0.0084746
14 country 0.0188216
14 campaign 0.0180033
14 political 0.0147300
14 american 0.0139116
14 america 0.0114566
14 wall 0.0106383
14 street 0.0090016
14 establishment 0.0090016
15 president 0.0170648
15 country 0.0147895
15 political 0.0147895
15 running 0.0136519
15 time 0.0113766
15 isis 0.0113766
15 region 0.0113766
## [1] 514.4031

Topic Modeling for Other Republican Nominees

## Joining, by = "word"
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : executive could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : january could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : missiles could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : prime could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : program could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : raised could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : recognize could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : redstate could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : resources could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : ronald could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : speech could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : strength could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : system could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : western could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : israel's could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : person could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : reason could not be fit on page. It will not be plotted.
## Warning in wordcloud(words = repub_word_cloud$word, freq = repub_word_cloud
## $n, : schedule could not be fit on page. It will not be plotted.

topic term beta
1 israel 0.0389462
1 america 0.0171821
1 president 0.0126002
1 nation 0.0114548
1 iran 0.0080183
1 united 0.0080183
1 missile 0.0080183
1 deal 0.0068729
1 administration 0.0068729
1 flights 0.0068729
1 hamas 0.0068729
1 terrorist 0.0068729
1 time 0.0068729
1 ban 0.0057274
1 congress 0.0057274
1 iranian 0.0057274
1 minister 0.0057274
1 nuclear 0.0057274
1 prime 0.0057274
2 america 0.0415993
2 love 0.0300151
2 freedom 0.0276753
2 day 0.0261881
2 bring 0.0161453
2 country 0.0146262
2 child 0.0096425
2 celebrates 0.0095512
2 grandkids 0.0092946
2 november 0.0092009
2 government 0.0091981
2 stand 0.0085999
2 free 0.0083326
2 live 0.0081194
2 police 0.0078825
3 stood 0.0134228
3 conservative 0.0124640
3 campaign 0.0095877
3 president 0.0095877
3 win 0.0095877
3 candidates 0.0086290
3 republican 0.0086290
3 women 0.0086290
3 democrats 0.0086290
3 obama 0.0076702
3 candidate 0.0067114
3 leaders 0.0067114
3 time 0.0067114
3 issues 0.0067114
3 house 0.0067114
3 leading 0.0067114
3 debate 0.0067114
4 time 0.0275862
4 country 0.0229885
4 america 0.0183908
4 president 0.0183908
4 generation 0.0183908
4 win 0.0183908
4 tonight 0.0160920
4 children 0.0137931
4 nation 0.0137931
4 united 0.0137931
4 century 0.0137931
4 chance 0.0137931
4 nominee 0.0137931
4 story 0.0114943
4 told 0.0114943
4 parents 0.0114943
5 national 0.0988996
5 abused 0.0405330
5 america 0.0365984
5 terrorists 0.0330909
5 middle 0.0235261
5 deal 0.0230308
5 nuclear 0.0195255
5 bottom 0.0193219
5 isis 0.0171067
5 security 0.0139709
5 freedom 0.0134963
5 join 0.0116816
5 benefit 0.0113493
5 nato 0.0112136
5 support 0.0101105
6 freedom 0.0374384
6 means 0.0140378
6 love 0.0113480
6 government 0.0111102
6 stand 0.0095083
6 future 0.0090980
6 life 0.0089727
6 rights 0.0085954
6 dad 0.0084242
6 tonight 0.0080223
6 protect 0.0076686
6 hug 0.0076017
6 family 0.0073684
6 country 0.0072345
6 values 0.0070426
7 israel 0.0317003
7 security 0.0105668
7 support 0.0096061
7 jewish 0.0086455
7 iran 0.0067243
7 isis 0.0067243
7 nuclear 0.0067243
7 palestinian 0.0057637
7 allies 0.0057637
7 natan 0.0057637
7 deal 0.0048031
7 friends 0.0048031
7 world 0.0048031
7 build 0.0048031
7 reagan 0.0048031
7 community 0.0048031
7 israel’s 0.0048031
7 memorial 0.0048031
7 regional 0.0048031
8 freedom 0.0436926
8 america 0.0238598
8 choose 0.0147571
8 free 0.0132796
8 party 0.0113262
8 fighting 0.0088624
8 establishment 0.0088505
8 country 0.0085910
8 police 0.0085855
8 future 0.0085436
8 government 0.0085224
8 human 0.0082230
8 powerful 0.0079863
8 millions 0.0079440
8 unite 0.0078948
9 allies 0.0189349
9 world 0.0126369
9 values 0.0108388
9 america 0.0085074
9 isis 0.0079023
9 china 0.0072383
9 international 0.0072376
9 military 0.0071861
9 nato 0.0070862
9 russia 0.0063425
9 live 0.0063141
9 syria 0.0062985
9 intelligence 0.0062737
9 pacific 0.0054423
9 western 0.0054297
10 americans 0.0181406
10 words 0.0181406
10 world 0.0181406
10 time 0.0136054
10 hope 0.0113379
10 generation 0.0113379
10 freedom 0.0113379
10 forward 0.0090703
10 jobs 0.0090703
10 live 0.0090703
10 set 0.0090703
10 america 0.0090703
10 evil 0.0068027
10 free 0.0068027
10 question 0.0068027
10 unite 0.0068027
10 vision 0.0068027
10 washington 0.0068027
10 build 0.0068027
10 change 0.0068027
10 learned 0.0068027
10 led 0.0068027
10 outsider 0.0068027
10 past 0.0068027
10 politician 0.0068027
10 reagan 0.0068027
10 spirit 0.0068027
## [1] 414.6573